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fix: cargo fmt

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This commit is contained in:
Volodymyr Orlov
2020-06-05 17:52:03 -07:00
parent 685be04488
commit a2784d6345
52 changed files with 3342 additions and 2829 deletions
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src/linalg/lu.rs
+46 -52
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@@ -3,22 +3,21 @@
use std::fmt::Debug;
use std::marker::PhantomData;
use crate::math::num::FloatExt;
use crate::linalg::BaseMatrix;
use crate::math::num::FloatExt;
#[derive(Debug, Clone)]
pub struct LU<T: FloatExt, M: BaseMatrix<T>> {
LU: M,
pub struct LU<T: FloatExt, M: BaseMatrix<T>> {
LU: M,
pivot: Vec<usize>,
pivot_sign: i8,
singular: bool,
phantom: PhantomData<T>
phantom: PhantomData<T>,
}
impl<T: FloatExt, M: BaseMatrix<T>> LU<T, M> {
pub fn new(LU: M, pivot: Vec<usize>, pivot_sign: i8) -> LU<T, M> {
let (_, n) = LU.shape();
let (_, n) = LU.shape();
let mut singular = false;
for j in 0..n {
@@ -33,7 +32,7 @@ impl<T: FloatExt, M: BaseMatrix<T>> LU<T, M> {
pivot: pivot,
pivot_sign: pivot_sign,
singular: singular,
phantom: PhantomData
phantom: PhantomData,
}
}
@@ -63,24 +62,24 @@ impl<T: FloatExt, M: BaseMatrix<T>> LU<T, M> {
for i in 0..n_rows {
for j in 0..n_cols {
if i <= j {
U.set(i, j, self.LU.get(i, j));
U.set(i, j, self.LU.get(i, j));
} else {
U.set(i, j, T::zero());
}
}
}
U
}
pub fn pivot(&self) -> M {
let (_, n) = self.LU.shape();
let mut piv = M::zeros(n, n);
for i in 0..n {
piv.set(i, self.pivot[i], T::one());
}
piv
}
@@ -92,7 +91,7 @@ impl<T: FloatExt, M: BaseMatrix<T>> LU<T, M> {
}
let mut inv = M::zeros(n, n);
for i in 0..n {
inv.set(i, i, T::one());
}
@@ -106,7 +105,10 @@ impl<T: FloatExt, M: BaseMatrix<T>> LU<T, M> {
let (b_m, b_n) = b.shape();
if b_m != m {
panic!("Row dimensions do not agree: A is {} x {}, but B is {} x {}", m, n, b_m, b_n);
panic!(
"Row dimensions do not agree: A is {} x {}, but B is {} x {}",
m, n, b_m, b_n
);
}
if self.singular {
@@ -120,9 +122,9 @@ impl<T: FloatExt, M: BaseMatrix<T>> LU<T, M> {
X.set(i, j, b.get(self.pivot[i], j));
}
}
for k in 0..n {
for i in k+1..n {
for i in k + 1..n {
for j in 0..b_n {
X.sub_element_mut(i, j, X.get(k, j) * self.LU.get(i, k));
}
@@ -140,7 +142,7 @@ impl<T: FloatExt, M: BaseMatrix<T>> LU<T, M> {
}
}
}
for j in 0..b_n {
for i in 0..m {
b.set(i, j, X.get(i, j));
@@ -148,20 +150,16 @@ impl<T: FloatExt, M: BaseMatrix<T>> LU<T, M> {
}
b
}
}
pub trait LUDecomposableMatrix<T: FloatExt>: BaseMatrix<T> {
pub trait LUDecomposableMatrix<T: FloatExt>: BaseMatrix<T> {
fn lu(&self) -> LU<T, Self> {
self.clone().lu_mut()
}
fn lu_mut(mut self) -> LU<T, Self> {
let (m, n) = self.shape();
let (m, n) = self.shape();
let mut piv = vec![0; m];
for i in 0..m {
@@ -172,7 +170,6 @@ pub trait LUDecomposableMatrix<T: FloatExt>: BaseMatrix<T> {
let mut LUcolj = vec![T::zero(); m];
for j in 0..n {
for i in 0..m {
LUcolj[i] = self.get(i, j);
}
@@ -189,7 +186,7 @@ pub trait LUDecomposableMatrix<T: FloatExt>: BaseMatrix<T> {
}
let mut p = j;
for i in j+1..m {
for i in j + 1..m {
if LUcolj[i].abs() > LUcolj[p].abs() {
p = i;
}
@@ -205,50 +202,47 @@ pub trait LUDecomposableMatrix<T: FloatExt>: BaseMatrix<T> {
piv[j] = k;
pivsign = -pivsign;
}
if j < m && self.get(j, j) != T::zero() {
for i in j+1..m {
for i in j + 1..m {
self.div_element_mut(i, j, self.get(j, j));
}
}
}
}
LU::new(self, piv, pivsign)
}
fn lu_solve_mut(self, b: Self) -> Self {
self.lu_mut().solve(b)
}
self.lu_mut().solve(b)
}
}
#[cfg(test)]
mod tests {
mod tests {
use super::*;
use crate::linalg::naive::dense_matrix::*;
use crate::linalg::naive::dense_matrix::*;
#[test]
fn decompose() {
let a = DenseMatrix::from_array(&[&[1., 2., 3.], &[0., 1., 5.], &[5., 6., 0.]]);
let expected_L = DenseMatrix::from_array(&[&[1. , 0. , 0. ], &[0. , 1. , 0. ], &[0.2, 0.8, 1. ]]);
let expected_U = DenseMatrix::from_array(&[&[ 5., 6., 0.], &[ 0., 1., 5.], &[ 0., 0., -1.]]);
let expected_pivot = DenseMatrix::from_array(&[&[0., 0., 1.], &[0., 1., 0.], &[1., 0., 0.]]);
let lu = a.lu();
assert!(lu.L().approximate_eq(&expected_L, 1e-4));
assert!(lu.U().approximate_eq(&expected_U, 1e-4));
assert!(lu.pivot().approximate_eq(&expected_pivot, 1e-4));
fn decompose() {
let a = DenseMatrix::from_array(&[&[1., 2., 3.], &[0., 1., 5.], &[5., 6., 0.]]);
let expected_L = DenseMatrix::from_array(&[&[1., 0., 0.], &[0., 1., 0.], &[0.2, 0.8, 1.]]);
let expected_U = DenseMatrix::from_array(&[&[5., 6., 0.], &[0., 1., 5.], &[0., 0., -1.]]);
let expected_pivot =
DenseMatrix::from_array(&[&[0., 0., 1.], &[0., 1., 0.], &[1., 0., 0.]]);
let lu = a.lu();
assert!(lu.L().approximate_eq(&expected_L, 1e-4));
assert!(lu.U().approximate_eq(&expected_U, 1e-4));
assert!(lu.pivot().approximate_eq(&expected_pivot, 1e-4));
}
#[test]
fn inverse() {
let a = DenseMatrix::from_array(&[&[1., 2., 3.], &[0., 1., 5.], &[5., 6., 0.]]);
let expected = DenseMatrix::from_array(&[&[-6.0, 3.6, 1.4], &[5.0, -3.0, -1.0], &[-1.0, 0.8, 0.2]]);
let a_inv = a.lu().inverse();
println!("{}", a_inv);
assert!(a_inv.approximate_eq(&expected, 1e-4));
fn inverse() {
let a = DenseMatrix::from_array(&[&[1., 2., 3.], &[0., 1., 5.], &[5., 6., 0.]]);
let expected =
DenseMatrix::from_array(&[&[-6.0, 3.6, 1.4], &[5.0, -3.0, -1.0], &[-1.0, 0.8, 0.2]]);
let a_inv = a.lu().inverse();
println!("{}", a_inv);
assert!(a_inv.approximate_eq(&expected, 1e-4));
}
}
}